Bibliographic record
Abstract
accountability 308 adverse events advocacy groups and 249 autism 239-56 Canada and 270 HPV vaccine 211 Japan and 211, 220-9 liability 150 Mexico and oral Bacillus Calmette-Guérin (BCG) vaccine 130 oral polio vaccine (OPV) 132 diphtheria, pertussis and tetanus vaccine (DPT) 133 MMR vaccine 220-9, 239-56, 270 polio (paralysis) 85, 293, 296, 299 smallpox vaccine 262 surveillance of 194-6 tetanus-diphtheria vaccine 243-4 tuberculosis vaccine 263 see also BCG yellow fever vaccination 195 Africa yellow fever in 181-8, 196-8 see also specific countries Alma-Ata Declaration 67-70 Americas (the) see specific countries antibiotics 129, 132, 267 Asia 6, 24, 39-40, 101, 108 Asian flu 267-9 smallpox eradication 5, 19 see also specific countries autism 239-49 Bacille-Calmette-Guérin vaccine (BCG) 53-4, 61-5, 69-70, 127, 130, 134, 136-9, 210, 212, 218, 229, 295, 306 bacteriology 123-8, 139, 149, 177, 213 Bangladesh 19-41 beliefs hepatitis B transmission and 104-5 prayer 291 religious 55, 58-61, 291, 302 sanitation versus vaccination 59-60, 105
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.856 | 0.760 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".